You’ve probably heard it before; remember your time tracking! Maybe you wonder why... This is equally important no matter your position, whether you’re an executive or a regular team member. Time tracking is key to understand how you spend your time, personally and businesswise. It is key to productivity, insight and workflow. When you know which tasks take up the most time, not necessarily the ones that need the most effort or bring the most gain, you can begin to reflect on whether that time is actually well spent;

Is the task important enough to take up that specific amount of time?

Would the time have been more effectively used and beneficial for another task?

Did the task work towards a broader goal? (e.g., the business mission)

Did the task work towards a personal or career goal?

What did the task actually change?

When you’ve got some of these questions covered; it’s time to consider whether something could be changed for the better, making it more efficient; could it be re-organized, does the software or hardware need an update, did you have to wait on somebody or something in order to proceed. What annoyed you in the process? Change it. These are all important questions to ask for both yourself and your team. Rank the tasks based on importance, and allocate your time accordingly.

Benefits of time tracking

Personal insights

Business insights

Productivity increase

Higher effectivity and efficiency

Quality improvements, due to streamlined workflow

Transparency

Cost efficient

Makes you able to reflect, and adapt accordingly.

The insights you get from time tracking can often be an eye-opener. How much time do you actually spend browsing the web, looking through your inbox or trying to find that one document in a pile of folders. There are many automated software solutions available, which at least makes the digital time tracking close to an effortless experience.

RescueTime is an option that works across your devices, and tracks both your personal and business life; which websites and apps do you use the most, and categorizes it to provide valuable insights, incl. an overall productivity score. Based on this score you can compare your workflow on different days. What did work, and what did not work? Another way to do time tracking directly on tasks, is to use a project management solution. These make it easier to manage all of your tasks across the project and organization to provide you and your team with valuable insights.

One option could be our solution, Forecast. Forecast makes time tracking simple and intelligent by using artificial intelligence to predict future time estimations. The time is reported directly on each task by each team member, and the software makes sure to include it in future calculations to improve the time estimations. Insights is automatically generated through dynamic real-time reporting, and presented in a visual manner directly in the system.

The time spent is a key measure of resources needed. It shows whether a specific department needs more resources, in terms of workforce or another input, and it gives you insights on who provides the most value for the team. This is all valuable information both for the team and the organization as a whole. Maybe one person does most of the work. Maybe something needs to be changed in order to bring everybody to the same level. Maybe some would be more interested in relocating to another team in another department. These are all insights brought to the table by your time tracking efforts.

As a team member, use the time tracking to work towards your personal and shared goals. As an executive, use the time tracking insights to provide you with an accurate overview of your team peak, performance, overall well-being and productivity, allowing you to manage resources and distribute tasks evenly.

Major projects are necessary to make big changes, but often some of these projects risk to go over budget, overdue or fail completely. This is often partly due to inaccurate initial planning and estimations. Even for very experienced project managers, and teams as a whole it can be a mind-boggling task to attempt to get all of these factors accurate. This is where intelligent software comes into play. Humans are exceptionally good at tackling the soft-side of project management, and this part will probably not be possible to successfully assist by a machine anytime soon, but the hard-part on the other hand is very well conducted by hardware.

Project managers in both major private, and public organizations are faced with these problems on a daily-basis. How do you estimate time, budget and not least how the whole process is going to plan out - even before the project has begun its initial phases. Estimates like time spent on each feature of the project, budget allocated to each feature, utilization of team members (i.e. employees), and prevention of over-allocation.

Besides, the hard data initial planning - there are also often four other factors in play when a major, often public, IT-project is doomed to fail. These include, lack of a set specific goal of the project, lack of specification or what needs it should fulfill in the end, lack of involvement of the actual users, and last but not least changing requirements and needs during, and after the development and implementation stages. These are all major problems, since it can often take years to develop systems on a public scale, and at the same time they are sometimes following the waterfall-approach and delivered at the end stage. That’s usually not how IT-projects should be developed.

Most modern IT software projects are continually developed, adapted and controlled through an agile project management method. Agile makes sure that new requests are welcome, and that users are involved in the product development. It is open to new, or revised feature requirements, and thus hopefully serves a better product on a continuous basis. In an environment of rapid change and development it is paramount to operate with an agile mindset.

A 2016 report from the Project Management Institute (PMI), shows that for every 1 billion USD spent, 122 million of these will be wasted due to a lack of project performance. A further analysis by Geneca suggests that up to 75% of initiated projects are doomed to fail from the beginning. KeyedIN suggests that 50% of all Project Management Offices (PMOs) shutdown within the first three years, and fewer than 1/3 projects were successfully completed on time and budget in 2013, according to Standish Group. Furthermore a very crucial factor in project management is to have a set plan, stick to it as long as it makes sense, and track the progress on a continuous basis to know exactly where the specific project is in the process compared to what was initially planned out. Though, 1/3 projects (34%) do not have a set baseline to keep it all on track, according to Wellingtone. This obviously needs to change.

What exactly can you do, in order to avoid some of these problems?We made a simple list with things you should definitely take into consideration.

Intelligent estimationsUse intelligent software solutions to estimate and plan your projects. This way you're able to make better justified decisions, based on verified data, for your business.

Specify a project goalWith a shared goal in mind - everybody knows where the project should be heading. Thus, you make sure that the project stays on track, and actually gets the job done in the end.

Determine needs to fulfillDetermine which needs the end product should fulfill. Which gap is it exactly that this specific product should help to close. What should it improve, make easier, more effective, etc. This should usually align with the overall business mission.

Involve the actual usersWho knows best which needs they have? The end user.The actual user should always be involved in the development process. Feedback is crucial, and adaptation is needed.

Project management methodMake sure to use the right project management method. Agile is most often the best fit for projects which are influenced by rapid industry changes. Waterfall is often the best fit for more traditional projects that doesn't necessarily change requirements later on.

Below, we will provide you with a figure of just a chosen few of either completely failed projects, or projects that ended up overdue, and / or over budget. This happened at least partly due to the lack of inspection of some of the points mentioned above. The examples are collected from Denmark, UK and the US.

There are of course various reasons why some of these projects failed either completely or to a certain extend, but what is certain is that artificial intelligence could most likely have assisted the project, managers and teams in their work, and made a more solid foundation for the project to built upon.

Now, all failed projects are not just bad, and a total waste of resources. Many of these projects provide lessons learned, and might be included in another product later on. We always learn new stuff, and it’s certain that some projects will always fail, but with the assistance of artificial intelligence - it’s also certain that at least some of those risks can be limited or completely avoided in a much earlier stage, if applied and used correctly by all team members that is.

We at Forecast, are currently developing a brand new type of project management software that brings some of the more advanced features from major software solutions into a more simplified environment. Thus, making it easier for everybody to manage their projects in an effective manner. At the same time the everyday management is supported by artificial intelligence based on verified data, making your projects more reliable and your business decisions more justified. If this sounds like something you might like to try out - we are currently accepting signups through the form available here.

Artificial intelligence (A.I.) has taken the media by storm, with new groundbreaking accomplishments by global companies. Google’s DeepMind recently beat a world champion of Go, which is said to be the most advanced board game on this planet. Moreover, DeepMind is now able to assist doctors during surgery, detect risk of blindness in an early state to improve the chances of recovery, and other important breakthroughs such as natural language recognition, object detection in images, and face recognition.

Most recently the DeepMind team has been able to generate natural-sounding music and speech based on data from its neural network, WaveNet. A survey showed that the A.I.-generated voice sounded more natural to the sample group of both English and Mandarin Chinese speakers than Google’s other text-to-speech technologies developed by other means, though WaveNet was still not able to outperform the recorded voice of real human beings.

IBM’s Watson is able to, among other things, gather, analyze, and provide you with detailed insights into your personality based solely on data from your Twitter account. There are already many companies in this space, and the consumer will, in the coming months and years and with or without their knowledge, begin to benefit from some of these technological advances.

One feature that many consumers have already played around with are the personal mobile assistants, including Google Assistant, Apple Siri, Microsoft Cortana, Facebook M, and many others. These bots are already helping people perform daily tasks, saving time and energy by making photos searchable with objects and people present in them, uncluttering your inbox, and automatically generating subtitles for your videos. But this is still just the beginning.

One specific space ripe for A.I. help is the project management field — and thereby technically all industries. Major projects, whether on a private or governmental level, are prone to go overdue or over budget, sometimes both. This all comes down to inaccurate planning in the initial phase of the project. It’s an ideal target for machine learning.

Project managers face on a daily basis a large number of unknown factors that need to be taken into consideration before, during, and after the project: estimates, employee allocation and utilization, task management, and more. There are many unknown values to play around with, which often turns into too much information. A few examples from Denmark suggest that even very experienced entities encounter these problems, e.g. the Eurovision Song Contest in Copenhagen, Rejsekort (the Travel Card system for public transportation), and the national digital health journaling systems. There are many other examples from Denmark alone.

To help this problem, artificial intelligence and machine-learning technology are now beginning to penetrate the market for project management tools. Right now project managers are only able to base their decisions, estimates, and so forth on their own previous experience and cannot automatically benefit from the knowledge that the rest of the world’s project managers are dealing with. That is where artificial intelligence comes in. Intelligent software is able to grasp data from across organizations and various types of projects (whether private or public) and tasks, anonymize this data, and create an algorithm to more accurately estimate some of the unknown variables including the schedule, budget, and resource utilization.

For every piece of data added to the intelligent project management system, the A.I.-generated algorithm will be updated and improved. This results in better and more justified decisions from project managers, as well as the individual team members. In the end, providing and supporting more stable projects that stay on track makes your team able to deliver better projects in time and on budget.

Artificial intelligence (AI) is probably the most rapidly growing new type of technology, and will for sure create a new era of the modern world as we know it today. Modern AI simulates the constant processes going on in our bodies every second of our lives, the human brain and nervous system. The nervous system takes every little piece of information in, through all of your senses, analyzes it, and decides what to keep and what to let go of. You learn from the past, gain experience, to improve your future. This is an ongoing process, and through time you learn to make better decisions; your intuition learns to navigate the world - you automatically improve over time. The is the essence of artificial intelligence.

AI gets the same constant input through an inflow of data, which is stored in the neural network. The same principle, just another name. Data gets analyzed, and processed. Over time an algorithm is setup, and constantly changed a bit, in order to improve, and make better decisions in the future. Now the difference here is that modern AI systems never sleep, and moreover it gets input from often a large amount of people. This makes it able to improve the algorithm faster, and better since the changes are based on input from all of these users, instead of just one - in the case of the human brain.

It’s still early days for AI, but we do already see some great advances in how it can assist people in various different situations and industries. The health industry does already benefit from some of the early research. Google’s DeepMind assists physicians during surgery operations, and it’s now able to recognize early stages of blindness in people, which could potentially help doctors give the right medication, and in the end avoid that risk. Other examples of advances, but just as significant, are natural language recognition, which makes technology able to understand what you say, automatically subtitle a video for deaf people, or translate an ongoing conversation in real-time between you and and another person. We already see examples of these products, and they do actually work quite well. In the future, we could all talk our mother’s tongue, and just have a computer in our ear live translating the conversation.

Furthermore, object detection and face recognition already help people to automatically organize their pictures, make them searchable, so you can find that one picture with your significant other at the beach with a cocktail in your hand. Object detection is also already seen in various industries, for instance a cucumber manufacturer uses the technology to automatically determine a cucumber’s size, and thereby sort them into different categories, label them and it’s ready for the grocery store. Blind people use the technology to get a description of a picture on Facebook, or get the text read out loud for them - thus making smartphones available to a new group of people, and assist them in navigating a device that other people take for granted. This vanishes the need for a human assistant, thus increasing privacy and anonymity. The same technology could potentially be introduced in voting booths during elections.

There are many examples already now. One place where many of us have most likely already experienced some of the advantages of AI, is in the palm of your hand, the personal (mobile) assistants. Google Assistant, Apple’s Siri, Microsoft’s Cortana, Facebook’s M, etc. They are already out there, and ready to assist you in your daily life. Help you with time consuming tasks, unclutter your inbox, provide you with information about the departure of your next train, when you should leave to reach the office in time, or if there is a traffic jam on the way then provide you with an alternative route. For instance, Google Maps uses speed data from various devices to automatically detect traffic jams, where it starts and ends, and how long it will take to get through. Similarly, Facebook uses AI to determine what you should see in your personal news feed, and it’s in the same way in constant movement based on how you interact with your timeline. How long time you look at a specific post, if you tap it, like it, comment or just look at the comments. All of these things happen automatically in the background, a constant exchange between Facebook’s servers and your smartphone. This exchange of data should hopefully improve your experience with Facebook, and other services, to use them more, and in the end benefit from these improvements.

We, at Forecast, use data from various different organizations and projects in a similar way to constantly improve our AI-technology. Whenever a project manager or a team member enter some data into the Forecast system, there’s an inflow of data. This data is anonymized, and analyzed to improve the algorithm for everybody’s benefit. The algorithm is used to estimate some of the unknown values that teams are dealing with on a daily basis, time estimates, budget, scheduling and employee utilization, etc. Making you able to make better decisions, which are based on a more solid and justified foundation. This will hopefully lead to better and more profitable projects, in time and on budget.